智能系统学报2015，Vol.10Issue(5)：684-689,6.DOI:10.11992/tis.201410018
进化支持向量机模型及其在水质评估中的应用
Evolutionary support vector machine model and its application in water quality assessment
摘要
Abstract
A water quality assessment model is an effective tool for water quality planning, environmental water pol-lution control and environment management. In this paper, an evolutionary support vector machine ( SVM) model is developed by using genetic algorithm ( GA) to combine and optimize the radial basis kernel function parameter σand error penalty factor C of a SVM algorithm. This model is then extended to water quality assessment. To test the effectiveness of the proposed method, it is applied to a simulation on real data of the Songyuan and Harbin sections of the Songhua River, the Gansu section of the Yellow River, and the Jilin Huadian Guanmenlizi water reservoir. Simulation results show that, compared with the classical SVM method, the classification accuracy and generaliza-tion ability of the evolutionary support vector machine model for water quality assessment are improved.关键词
水质评估模型/支持向量机(SVM)/遗传算法(GA)/径向基核函数/惩罚因子Key words
water quality assessment model/support vector machine ( SVM)/genetic algorithms ( GA)/radial ba-sis kernel function/penalty factor分类
信息技术与安全科学引用本文复制引用
钱云,梁艳春,翟天放,刘洪志,时小虎..进化支持向量机模型及其在水质评估中的应用[J].智能系统学报,2015,10(5):684-689,6.基金项目
吉林省科技发展计划项目(20130206003SF). （20130206003SF）
